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Resample Function

get(connection, parameters_dict)

An RTDIP Resampling function in spark to resample data by querying databricks SQL warehouses using a connection and authentication method specified by the user. This spark resample function will return a resampled dataframe.

The available connectors by RTDIP are Databricks SQL Connect, PYODBC SQL Connect, TURBODBC SQL Connect.

The available authentcation methods are Certificate Authentication, Client Secret Authentication or Default Authentication. See documentation.

This function requires the user to input a dictionary of parameters. (See Attributes table below)

Parameters:

Name Type Description Default
connection object

Connection chosen by the user (Databricks SQL Connect, PYODBC SQL Connect, TURBODBC SQL Connect)

 required
parameters_dict dict

A dictionary of parameters (see Attributes table below)

 required

Attributes:

Name Type Description
business_unit str

Business unit of the data
region str

Region
asset str

Asset
data_security_level str

Level of data security
data_type str

Type of the data (float, integer, double, string)
tag_names list

List of tagname or tagnames ["tag_1", "tag_2"]
start_date str

Start date (Either a date in the format YY-MM-DD or a datetime in the format YYY-MM-DDTHH:MM:SS or specify the timezone offset in the format YYYY-MM-DDTHH:MM:SS+zz:zz)
end_date str

End date (Either a date in the format YY-MM-DD or a datetime in the format YYY-MM-DDTHH:MM:SS or specify the timezone offset in the format YYYY-MM-DDTHH:MM:SS+zz:zz)
sample_rate str

The resampling rate (numeric input)
sample_unit str

The resampling unit (second, minute, day, hour)
agg_method str

Aggregation Method (first, last, avg, min, max)
include_bad_data bool

Include "Bad" data points with True or remove "Bad" data points with False

Returns:

Name Type Description
DataFrame pd.DataFrame

A resampled dataframe.
Source code in src/sdk/python/rtdip_sdk/queries/time_series/resample.py 
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def get(connection: object, parameters_dict: dict) -> pd.DataFrame:
    '''
    An RTDIP Resampling function in spark to resample data by querying databricks SQL warehouses using a connection and authentication method specified by the user. This spark resample function will return a resampled dataframe.

    The available connectors by RTDIP are Databricks SQL Connect, PYODBC SQL Connect, TURBODBC SQL Connect.

    The available authentcation methods are Certificate Authentication, Client Secret Authentication or Default Authentication. See documentation.

    This function requires the user to input a dictionary of parameters. (See Attributes table below)

    Args:
        connection: Connection chosen by the user (Databricks SQL Connect, PYODBC SQL Connect, TURBODBC SQL Connect)
        parameters_dict: A dictionary of parameters (see Attributes table below)

    Attributes:
        business_unit (str): Business unit of the data
        region (str): Region
        asset (str):  Asset
        data_security_level (str): Level of data security
        data_type (str): Type of the data (float, integer, double, string)
        tag_names (list): List of tagname or tagnames ["tag_1", "tag_2"]
        start_date (str): Start date (Either a date in the format YY-MM-DD or a datetime in the format YYY-MM-DDTHH:MM:SS or specify the timezone offset in the format YYYY-MM-DDTHH:MM:SS+zz:zz)
        end_date (str): End date (Either a date in the format YY-MM-DD or a datetime in the format YYY-MM-DDTHH:MM:SS or specify the timezone offset in the format YYYY-MM-DDTHH:MM:SS+zz:zz)
        sample_rate (str): The resampling rate (numeric input)
        sample_unit (str): The resampling unit (second, minute, day, hour)
        agg_method (str): Aggregation Method (first, last, avg, min, max)
        include_bad_data (bool): Include "Bad" data points with True or remove "Bad" data points with False

    Returns:
        DataFrame: A resampled dataframe.
    '''
    if isinstance(parameters_dict["tag_names"], list) is False:
        raise ValueError("tag_names must be a list")

    try:
        query = _query_builder(parameters_dict)

        try:
            cursor = connection.cursor()
            cursor.execute(query)
            df = cursor.fetch_all()
            cursor.close()
            return df
        except Exception as e:
            logging.exception('error returning dataframe')
            raise e

    except Exception as e:
        logging.exception('error with resampling function')
        raise e

Example

from rtdip_sdk.authentication.azure import DefaultAuth
from rtdip_sdk.connectors import DatabricksSQLConnection
from rtdip_sdk.queries import resample

auth = DefaultAuth().authenticate()
token = auth.get_token("2ff814a6-3304-4ab8-85cb-cd0e6f879c1d/.default").token
connection = DatabricksSQLConnection("{server_hostname}", "{http_path}", token)

parameters = {
    "business_unit": "Business Unit",
    "region": "Region", 
    "asset": "Asset Name", 
    "data_security_level": "Security Level", 
    "data_type": "float", #options:["float", "double", "integer", "string"]
    "tag_names": ["tag_1", "tag_2"], #list of tags
    "start_date": "2023-01-01", #start_date can be a date in the format "YYYY-MM-DD" or a datetime in the format "YYYY-MM-DDTHH:MM:SS" or specify the timezone offset in the format "YYYY-MM-DDTHH:MM:SS+zz:zz"
    "end_date": "2023-01-31", #end_date can be a date in the format "YYYY-MM-DD" or a datetime in the format "YYYY-MM-DDTHH:MM:SS" or specify the timezone offset in the format "YYYY-MM-DDTHH:MM:SS+zz:zz"
    "sample_rate": "1", #numeric input
    "sample_unit": "hour", #options: ["second", "minute", "day", "hour"]
    "agg_method": "first", #options: ["first", "last", "avg", "min", "max"]
    "include_bad_data": True, #options: [True, False]
}
x = resample.get(connection, parameters)
print(x)

This example is using DefaultAuth() and DatabricksSQLConnection() to authenticate and connect. You can find other ways to authenticate here. The alternative built in connection methods are either by PYODBCSQLConnection(), TURBODBCSQLConnection() or SparkConnection().

Note

server_hostname and http_path can be found on the SQL Warehouses Page.